1.0 CITE-seq ADT PBMC and Plaque

This notebook displays interactive heatmaps of single cell antibody derived tag data from plaque and PBMC from the same subject. The data has been UMI normalized and Z-scored - please see manuscript for additional information.

In [1]:
from clustergrammer2 import net
df = {}
In [2]:
net.load_file('../data/citeseq_adt_pbmc.txt')
df['pbmc'] = net.export_df()
print('pbmc', df['pbmc'].shape)

net.load_file('../data/citeseq_adt_plaque.txt')
df['plaque'] = net.export_df()
print('plaque', df['plaque'].shape)

net.load_file('../data/citeseq_adt_merge.txt')
df['merged'] = net.export_df()
print('pbmc and plaque', df['merged'].shape)

pbmc (21, 3589)
plaque (21, 1643)
pbmc and plaque (21, 5232)
In [3]:
cat_colors = net.load_json_to_dict('../data/cite-seq_cat_colors.json')
net.set_cat_colors(cat_colors=cat_colors, axis='col', cat_index=1, cat_title='Tissue')
net.set_cat_colors(cat_colors=cat_colors, axis='col', cat_index=2, cat_title='Cell Type')

PBMC ADT

In [4]:
net.load_df(df['pbmc'])
net.widget()

Plaque ADT

In [5]:
net.load_df(df['plaque'])
net.widget()

PBMC and Plaque ADT

In [6]:
net.load_df(df['merged'])
net.widget()
In [ ]: